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A 3D MRI Brain image Segmentation and Reconstruction System Based on Augmented Reality Technology 10th

A 3D MRI Brain Image Segmentation and Reconstruction System ...

引用

10th China Health Information processing conference, CHIP 2024

作者： Zhao, Wang Lu, Peixin Hu, LianTing Lu, Long School of Management Engineering Henan University of Engineering Zhengzhou China School of Safety Science and Emergency Management Wuhan University of Technology Wuhan China Guangdong Provincial People’s Hospital Guangzhou China School of Information Management Wuhan University Wuhan China The Center for Healthcare Big Data Research The Big Data Institute Wuhan University Wuhan China Institute of Pediatrics Guangzhou Women and Children’s Medical Center Guangzhou Medical University Guangzhou China School of Public Health Wuhan University Wuhan China

ISBN: (纸本)9789819637546

Background With the rapid development of information technology and the digitization of medical devices, various diseases require the use of medical imaging equipment for diagnosis. At present, various medical imaging diagnostic equipment such as CT and nuclear magnetic resonance can provide two-dimensional planar images of diseases. Doctors urgently need to accurately determine the spatial location, size, geometry, and spatial relationship with the surrounding tissue. Therefore, it is very important to use computer technology to segment 3D MRI images, determine the location of lesions, and then perform 3D reconstruction. Method At present, automatic recognition and marking of brain images are displayed in two dimensions. Therefore, it is necessary to use 3D visualization technology for reconstruction. In addition, it can be combined with virtual and real, and some additional information is superimposed on the brain image for integrated display. In addition, a combination of virtual and real needs to be superimposed, and some additional information is superimposed on the brain image for integrated display. The research focus of this paper includes two main parts: disease segmentation and 3D reconstruction visualization. Firstly, the disease segmentation method based on 3D MRI brain image files was designed, and then the feature extraction and 3D reconstruction functions were designed. Thereby forming a complete process of disease region segmentation and three-dimensional reconstruction. Results This study is based on a three-dimensional MRI brain image segmentation algorithm. The algorithm is advanced in technology, high in accuracy, and can effectively identify the location of the disease. Then, this study used the Unity tool to implement a three-dimensional reconstruction and visual display program for brain image disease segmentation. Therefore, the doctor can quickly and intuitively grasp the spatial information inside the brain and the information of the lesion

关键词： image segmentation

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Looking for intelligent image treatment and manipulation: An information processing approach

Looking for intelligent image treatment and manipulation: An...

引用

Joint Meeting of the 14th International Workshop on Systems, Signals and image processing/EURASIP conference Focused on Speech and image processing, Multimedia communications and Services

作者： Diamant, Emanuel VIDIA Mant IL-55100 Kiriat Ono Israel

ISBN: (纸本)9789612480363

We are living in the Information Age, and information has become a critically important component of our life. Due to the success of the Internet, the amount of available information, including immense volumes of visual information, is growing explosively. Therefore means for its faultless circulation and handling are urgently required. Considerable research efforts are dedicated today to address this necessity, but they are seriously hampered by the lack of a common agreement about "What actually is visual information?" Without answering this question, all our remarkable efforts inevitably end up as a plain alchemy. I am trying to rind out a remedy for this bizarre and absurd situation. I propose my own definition of information (derived from the Kolmogorov's complexity theory), and from this point of view, attempt to revise the state of the art of contemporary image processing convention.

关键词： visual information image information processing image understanding CBIR and image search

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Real-time Learned image Codec on FPGA

Real-time Learned Image Codec on FPGA

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Sun, Heming Yi, Qingyang Lin, Fangzheng Yu, Lu Katto, Jiro Fujita, Masahiro Waseda Univ Tokyo Japan Zhejiang Univ Hangzhou Zhejiang Peoples R China JST PRESTO Kawaguchi Saitama Japan Univ Tokyo Tokyo Japan AIST Tsukuba Ibaraki Japan

This demo paper gives a real-time learned image codec on FPGA. By using Xilinx VCU128, the proposed system reaches 720P@30fps codec, which is 7.76x faster than prior work.

ISBN: (纸本)9781665475921

This demo paper gives a real-time learned image codec on FPGA. By using Xilinx VCU128, the proposed system reaches 720P@30fps codec, which is 7.76x faster than prior work.

关键词： image coding neural network FPGA

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A Marked Point Process Model For visual Perceptual Groups Extraction

A Marked Point Process Model For Visual Perceptual Groups Ex...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Mbarki, Amal Naouai, Mohamed Univ Tunis EL MANAR Fac Sci Tunis Tunis Tunisia

ISBN: (纸本)9781728180687

Perceptual organization is the process of assigning each part of a scene to a specified association of features to be a part of the same organization. In the twenty century, Gestalt psychologists formalized how image features tend to be grouped by giving a set of organizing principles. In this paper, we propose an approach for the detection of perceptual groups in an image. We are mainly interested in features grouped by the proximity law of Gestalt. We conceive an object-based model within a stochastic framework using a marked point process (MPP). We use a Bayesian learning method to extract perceptual groups in a scene. The proposed model tested on synthetic images proves the efficient detection of perceptual groups in noisy images.

关键词： visual perception perceptual organisation image processing marked point process

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Learning to Fly with a Video Generator

Learning to Fly with a Video Generator

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IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Chia-Chun Chung Wen-Hsiao Peng Teng-Hu Cheng Chia-Hau Yu Natl Yang Ming Chiao Tung Univ Hsinchu Taiwan

ISBN: (纸本)9781728185514

This paper demonstrates a model-based reinforcement learning framework for training a self-flying drone. We implement the Dreamer proposed in a prior work as an environment model that responds to the action taken by the drone by predicting the next video frame as a new state signal. The Dreamer is a conditional video sequence generator. This model-based environment avoids the time-consuming interactions between the agent and the environment, speeding up largely the training process. This demonstration showcases for the first time the application of the Dreamer to train an agent that can finish the racing task in the Airsim simulator.

关键词： Training visual communication image processing Atmospheric modeling Video sequences Reinforcement learning Predictive models

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Intelligent Reflection Elimination Imaging Device based on Polarizer

Intelligent Reflection Elimination Imaging Device based on P...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Chen, Xinru Liu, Hang Hu, Menghan Zhang, Lejing Li, Yunmian East China Normal Univ Shanghai Peoples R China Ruian Dawan Polaroid Mat Technol CO LTD Minnetonka MN USA

ISBN: (纸本)9781665475921

Glass reflection is a problem when taking photos through glass windows or showcases. As the visual quality of captured image can be enhanced by removing reflection, we develop an intelligent reflection elimination imaging device based on polarizer to minimize reflection effect on the images. The system mainly consists of a polarizing module, an image analysis module and a reflection removal module. The users can hold the device and capture images with minimum reflection whether in the day or night. The demo video is available at: https://***/10.6084/***.19687830.v1.

关键词： reflection removal polarized imaging image enhancement

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Geometric-visual descriptor for improved image based localization

Geometric-visual descriptor for improved image based localiz...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Ouni, Achref Royer, Eric Chevaldonne, Marc Dhome, Michel Univ Clermont Auvergne Inst Pascal Clermont Ferrand France

ISBN: (纸本)9781728180687

This paper addresses the problem of image based localization. The goal is to find quickly and accurately the relative pose from a query taken from a stereo camera and a map obtained using visual SLAM which contains poses and 3D points associated to descriptors. In this paper we introduce a new method that leverages the stereo vision by adding geometric information to visual descriptors. This method can be used when the vertical direction of the camera is known (for example on a wheeled robot). This new geometric visual descriptor can be used with several image based localization algorithms based on visual words. We test the approach with different datasets (indoor, outdoor) and we show experimentally that the new geometricvisual descriptor improves standard image based localization approaches.

关键词： Descriptors Retrieval images Pose estimation Localization

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A Deep Learning-based Audio-in-image Watermarking Scheme

A Deep Learning-based Audio-in-Image Watermarking Scheme

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Das, Arjon Zhong, Xin Univ Nebraska Omaha Dept Comp Sci Omaha NE 68182 USA

ISBN: (纸本)9781728185514

This paper presents a deep learning-based audio-in-image watermarking scheme. Audio-in-image watermarking is the process of covertly embedding and extracting audio watermarks on a cover-image. Using audio watermarks can open up possibilities for different downstream applications. For the purpose of implementing an audio-in-image watermarking that adapts to the demands of increasingly diverse situations, a neural network architecture is designed to automatically learn the watermarking process in an unsupervised manner. In addition, a similarity network is developed to recognize the audio watermarks under distortions, therefore providing robustness to the proposed method. Experimental results have shown high fidelity and robustness of the proposed blind audio-in-image watermarking scheme.

关键词： Audio-in-image watermarking deep learning neural networks robustness

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Scalable Privacy in Multi-Task image Compression

Scalable Privacy in Multi-Task Image Compression

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Alvar, Saeed Ranjbar Bajic, Ivan, V Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada

ISBN: (纸本)9781728185514

Learning-based compression systems have shown great potential for multi-task inference from their latent-space representation of the input image. In such systems, the decoder is supposed to be able to perform various analyses of the input image, such as object detection or segmentation, besides decoding the image. At the same time, privacy concerns around visual analytics have grown in response to the increasing capabilities of such systems to reveal private information. In this paper, we propose a method to make latent-space inference more privacy-friendly using mutual information-based criteria. In particular, we show how organizing and compressing the latent representation of the image according to task-specific mutual information can make the model maintain high analytics accuracy while becoming less able to reconstruct the input image and thereby reveal private information.

关键词： Learning-based compression privacy mutual information

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Motion Estimation for Quanta image Sensors Using Spatio-Temporal Priors

Motion Estimation for Quanta Image Sensors Using Spatio-Temp...

引用

2024 conference on visual communications and image processing

作者： Fukawa, Hiroya Kurihara, Kosuke Maeda, Yoshihiro Sato, Shunichi Hamamoto, Takayuki Tokyo Univ Sci Tokyo 1258585 Japan Shibaura Inst Technol Tokyo 1358548 Japan

ISBN: (纸本)9798331529543;9798331529550

Quanta image sensors are a novel paradigm in image sensor technology. Their direct application to quanta image sensors-based imaging systems is challenging because a bit-plane image is a set of binary images. In this paper, we introduce spatiotemporal priors based on the intensity invariance and smoothness characteristics of the motion vector. Specifically, we model when the image sequences align with the correct motion vector, the spatiotemporal structure becomes more consistent. Moreover, the spatial smoothness prior is incorporated through the smoothing filtering of the evaluation metrics of motion vector candidates. The experimental results show that the proposed method is more effective than conventional methods.

关键词： motion estimation quanta image sensors bit-plane images spatio-temporal prior

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